Radar having antennas arranged at horizontal and vertical intervals
US-12148984-B2 · Nov 19, 2024 · US
US9274221B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9274221-B2 |
| Application number | US-201313756606-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 1, 2013 |
| Priority date | Feb 1, 2013 |
| Publication date | Mar 1, 2016 |
| Grant date | Mar 1, 2016 |
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A method for remote object sensing on-board a vehicle includes employing compressive sensing to analyze a waveform originating from an on-vehicle low-resolution radar imaging system and reflected from a remote object. The compressive sensing includes generating a matrix including a temporal projection, a Fourier transform, and an integral term configured to analyze the reflected waveform. Leading and trailing edges of the remote object are identified by employing a norm minimization procedure to reconstruct a range profile based upon the reflected waveform analyzed by the compressive sensing.
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The invention claimed is: 1. A method for remote object sensing on-board a vehicle, comprising: operating an analog-to-digital (A/D) converter at a sampling rate proportional to a compressibility of sensed objects to generate a digitized form of an on-vehicle low-resolution radar imaging system and reflected from a remote object; within a signal processor: employing compressive sensing to analyze the digitized form of the waveform originating from an on-vehicle low-resolution radar imaging system and reflected from the remote object, said compressive sensing including generating a matrix comprising a temporal projection which is predetermined in an off-line environment, a Fourier transform, and an integral term configured to analyze the reflected waveform; and identifying leading and trailing edges of the remote object by employing a norm minimization procedure to reconstruct a range profile based upon the reflected waveform analyzed by said compressive sensing; wherein employing a norm minimization procedure includes finding a minimum of the reflected waveform employing linear programming; and providing an estimate of an actual location of the remote object based on the identified leading and trailing edges of the remote object. 2. The method of claim 1 , wherein said waveform originating from the on-vehicle low-resolution radar imaging system comprises a reflected linear frequency modulation (LFM) waveform. 3. The method of claim 2 , wherein said radar imaging system comprises a low bandwidth radar device, and said LFM waveform comprises a high frequency waveform that is less than 200 MHz. 4. The method of claim 1 , wherein the norm minimization procedure comprises an Ll norm minimization procedure. 5. The method of claim 1 , wherein said radar imaging system comprises a low bandwidth radar device configured to monitor a field of view relative to the vehicle. 6. The method of claim 5 , wherein said field of view comprises a front view relative to the vehicle. 7. The method of claim 5 , wherein said field of view comprises a side view relative to the vehicle. 8. The method of claim 1 , wherein compressive sensing including generating a matrix comprising the temporal projection, the Fourier transform, and the integral term configured to analyze the reflected waveform comprises employing compressive sensing to determine a measurement matrix Φ applied to the reflected waveform, wherein the measurement matrix Φ is represented by the following relationship: Φ=[0 I 0]*[ F]*[It] wherein [0 I 0] is a temporal projection matrix, [F] is a Fourier transform matrix, and [It] is an integral term. 9. The method of claim 8 , wherein said measurement matrix Φ applied to the reflected waveform is determined in a derivative space. 10. The method of claim 1 , wherein identifying leading and trailing edges of the remote object comprises employing an Ll norm minimization procedure including finding a minimum of the reflected waveform ( ) employing linear programming executing in accordance with the following relationship: min x ^ ∈ R N x ^ 1 1 subject to ∥ξ∥ 1 2 ≦ε wherein ε is a small number less than one and approaching zero, and ξ= y−Φ . 11. A method for remote object sensing on-board a vehicle employing a low-resolution radar imaging system, comprising: operating an analog-to-digital (A/D) converter at a sampling rate proportional to a compressibility of sensed objects to generate a digitized form of a linear frequency modulation (LFM) waveform generated by the low-resolution radar imaging system and reflected from a remote object; within a signal processor: employing compressive sensing to analyze the digitized form of the LFM waveform generated by the low-resolution radar imaging system and reflected from the remote object, said compressive sensing including determining a measurement matrix for the remote object in a derivative space based upon a temporal projection which is predetermined in an off-line environment, a Fourier transform, and an integral term; and identifying leading and trailing edges of the remote object by employing a norm minimization procedure to reconstruct a range profile based upon the measurement matrix for the remote object in the derivative space; wherein employing a norm minimization procedure includes finding a minimum of the reflected waveform employing linear programming; and providing an estimate of an actual location of the remote object based on the identified leading and trailing edges of the remote object. 12. The method of claim 11 , wherein the norm minimization procedure comprises an Ll norm minimization procedure. 13. The method of claim 11 , wherein determining the measurement matrix for the remote object comprises determining a measurement matrix Φ applied to the reflected LFM waveform wherein the measurement matrix Φ is represented by the following relationship: Φ=[0 I 0]*[ F]*[It] wherein [0 I 0] is a temporal projection matrix, [F] is a Fourier transform matrix, and [It] is an integral term. 14. The method of claim 11 , wherein identifying leading and trailing edges of the remote object comprises employing an Ll norm minimization procedure including finding a minimum of the reflected waveform ( ) employing linear programming executing in accordance with the following relationship: min x ^ ∈ R N x ^ 1 1 subject to ∥ξ∥ 1 2 ≦ε wherein ε is a small number less than one and approaching zero, and ξ= y−Φ .
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